[Review of the book <em>Introduction to the New Testament, Vol. 2: History and Literature of Early Christianity</em>, by H. Koester]
Bibliographic record
Abstract
The publication of this book completes the second edition of Helmut Koester’s important two-volume introduction to early Christian literature and history, published originally in 1982. Like the second edition of the first volume, which appeared in 1995, this edition seeks to make current the now classic and well-known introductory volume, while maintaining its structure and organization. After covering the formation of the canon, text critical issues and an all too brief introduction to methods—only source, form, tradition, narrative and rhetorical criticism are discussed, the latter two being new to this edition—texts are discussed in chronological and geographical sequence, beginning with traditions about John the Baptist, Jesus and Paul, then covering Palestine and Syria (where he locates both the Gospels of Mark, Matthew and John), and Asia, Macedonia, Greece and Rome. The book is less an introduction to New Testament writings than it is an attempt to paint a comprehensive picture of the development of early Christianity, creating a map of the relationships between the various texts, both canonical and non- canonical. Although one can disagree with the shape of the map and where some of the texts are placed in relation to others, it is extraordinarily useful as a place to start or a point of reference.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.036 | 0.016 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".